
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import zipfile
import cv2
from skimage import io

import tensorflow as tf
from tensorflow.python.keras import Sequential
from tensorflow.keras import layers, optimizers
from tensorflow.keras.layers import *
from tensorflow.keras.models import Model
from tensorflow.keras.initializers import glorot_uniform
from tensorflow.keras.utils import plot_model
from tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping, ModelCheckpoint, LearningRateScheduler
import tensorflow.keras.backend as K

import random
import glob
from sklearn.preprocessing import StandardScaler, normalize
from IPython.display import display


data = pd.read_csv('../desktop/lgg-mri-segmentation/kaggle_3m/data.csv')
data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 110 entries, 0 to 109
Data columns (total 18 columns):
 #   Column                     Non-Null Count  Dtype  
---  ------                     --------------  -----  
 0   Patient                    110 non-null    object 
 1   RNASeqCluster              92 non-null     float64
 2   MethylationCluster         109 non-null    float64
 3   miRNACluster               110 non-null    int64  
 4   CNCluster                  108 non-null    float64
 5   RPPACluster                98 non-null     float64
 6   OncosignCluster            105 non-null    float64
 7   COCCluster                 110 non-null    int64  
 8   histological_type          109 non-null    float64
 9   neoplasm_histologic_grade  109 non-null    float64
 10  tumor_tissue_site          109 non-null    float64
 11  laterality                 109 non-null    float64
 12  tumor_location             109 non-null    float64
 13  gender                     109 non-null    float64
 14  age_at_initial_pathologic  109 non-null    float64
 15  race                       108 non-null    float64
 16  ethnicity                  102 non-null    float64
 17  death01                    109 non-null    float64
dtypes: float64(15), int64(2), object(1)
memory usage: 15.6+ KB


data_map = []
for sub_dir_path in glob.glob("../desktop/lgg-mri-segmentation/kaggle_3m/"+"*"):
    #if os.path.isdir(sub_path_dir):
    try:
        dir_name = sub_dir_path.split('/')[-1]
        for filename in os.listdir(sub_dir_path):
            image_path = sub_dir_path + '/' + filename
            data_map.extend([dir_name, image_path])
    except Exception as e:
        print(e)

[WinError 267] The directory name is invalid: '../desktop/lgg-mri-segmentation/kaggle_3m\\data.csv'
[WinError 267] The directory name is invalid: '../desktop/lgg-mri-segmentation/kaggle_3m\\README.md'


df = pd.DataFrame({"patient_id" : data_map[::2],
                   "path" : data_map[1::2]})
df.head()


df_imgs = df[~df['path'].str.contains("mask")]
df_masks = df[df['path'].str.contains("mask")]

# File path line length images for later sorting
BASE_LEN = 86 # len(/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_ <-!!!43.tif)
END_IMG_LEN = 4 # len(/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_43 !!!->.tif)
END_MASK_LEN = 9 # (/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_43 !!!->_mask.tif)


x = len('/kaggle/input/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_ <-!!!43.tif')


y = len('../desktop/lgg-mri-segmentation/kaggle_3m/TCGA_DU_6404_19850629/TCGA_DU_6404_19850629_ <-!!!43.tif')


z = x-y
z

3


# Data sorting
imgs = sorted(df_imgs["path"].values, key=lambda x : int(x[BASE_LEN:-END_IMG_LEN]))


masks = sorted(df_masks["path"].values, key=lambda x : int(x[BASE_LEN:-END_MASK_LEN]))

# Sorting check
idx = random.randint(0, len(imgs)-1)
print("Path to the Image:", imgs[idx], "\nPath to the Mask:", masks[idx])

Path to the Image: ../desktop/lgg-mri-segmentation/kaggle_3m\TCGA_DU_5872_19950223/TCGA_DU_5872_19950223_61.tif 
Path to the Mask: ../desktop/lgg-mri-segmentation/kaggle_3m\TCGA_DU_5872_19950223/TCGA_DU_5872_19950223_61_mask.tif


# Final dataframe
brain_df = pd.DataFrame({"patient_id": df_imgs.patient_id.values,
                         "image_path": imgs,
                         "mask_path": masks
                        })
def pos_neg_diagnosis(mask_path):
    value = np.max(cv2.imread(mask_path))
    if value > 0 : 
        return 1
    else:
        return 0
    
brain_df['mask'] = brain_df['mask_path'].apply(lambda x: pos_neg_diagnosis(x))
brain_df


count = 0
i = 0
fig,axs = plt.subplots(12,3, figsize=(20,50))
for mask in brain_df['mask']:
    if (mask==1):
        img = io.imread(brain_df.image_path[i])
        axs[count][0].title.set_text("Brain MRI")
        axs[count][0].imshow(img)
        
        mask = io.imread(brain_df.mask_path[i])
        axs[count][1].title.set_text("Mask")
        axs[count][1].imshow(mask, cmap='gray')
        
        img[mask==255] = (0,255,150)  # change pixel color at the position of mask
        axs[count][2].title.set_text("MRI with Mask")
        axs[count][2].imshow(img)
        count +=1
    i += 1
    if (count==12):
        break
        
fig.tight_layout()


brain_df_train = brain_df.drop(columns=['patient_id'])
# Convert the data in mask column to string format, to use categorical mode in flow_from_dataframe
brain_df_train['mask'] = brain_df_train['mask'].apply(lambda x: str(x))
brain_df_train.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3929 entries, 0 to 3928
Data columns (total 3 columns):
 #   Column      Non-Null Count  Dtype 
---  ------      --------------  ----- 
 0   image_path  3929 non-null   object
 1   mask_path   3929 non-null   object
 2   mask        3929 non-null   object
dtypes: object(3)
memory usage: 92.2+ KB


from sklearn.model_selection import train_test_split

train, test = train_test_split(brain_df_train, test_size=0.15)


from keras_preprocessing.image import ImageDataGenerator

datagen = ImageDataGenerator(rescale=1./255., validation_split=0.1)

train_generator = datagen.flow_from_dataframe(train,
                                              directory='./',
                                              x_col='image_path',
                                              y_col='mask',
                                              subset='training',
                                              class_mode='categorical',
                                              batch_size=16,
                                              shuffle=True,
                                              target_size=(256,256)
                                             )
valid_generator = datagen.flow_from_dataframe(train,
                                              directory='./',
                                              x_col='image_path',
                                              y_col='mask',
                                              subset='validation',
                                              class_mode='categorical',
                                              batch_size=16,
                                              shuffle=True,
                                              target_size=(256,256)
                                             )
test_datagen = ImageDataGenerator(rescale=1./255.)
test_generator = test_datagen.flow_from_dataframe(test,
                                                  directory='./',
                                                  x_col='image_path',
                                                  y_col='mask',
                                                  class_mode='categorical',
                                                  batch_size=16,
                                                  shuffle=False,
                                                  target_size=(256,256)
                                                 )

Found 3006 validated image filenames belonging to 2 classes.
Found 333 validated image filenames belonging to 2 classes.
Found 590 validated image filenames belonging to 2 classes.


from tensorflow.keras.applications.resnet50 import ResNet50
clf_model = ResNet50(weights='imagenet', include_top=False, input_tensor=Input(shape=(256,256,3)))
clf_model.summary()

Model: "resnet50"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_1 (InputLayer)           [(None, 256, 256, 3  0           []                               
                                )]                                                                
                                                                                                  
 conv1_pad (ZeroPadding2D)      (None, 262, 262, 3)  0           ['input_1[0][0]']                
                                                                                                  
 conv1_conv (Conv2D)            (None, 128, 128, 64  9472        ['conv1_pad[0][0]']              
                                )                                                                 
                                                                                                  
 conv1_bn (BatchNormalization)  (None, 128, 128, 64  256         ['conv1_conv[0][0]']             
                                )                                                                 
                                                                                                  
 conv1_relu (Activation)        (None, 128, 128, 64  0           ['conv1_bn[0][0]']               
                                )                                                                 
                                                                                                  
 pool1_pad (ZeroPadding2D)      (None, 130, 130, 64  0           ['conv1_relu[0][0]']             
                                )                                                                 
                                                                                                  
 pool1_pool (MaxPooling2D)      (None, 64, 64, 64)   0           ['pool1_pad[0][0]']              
                                                                                                  
 conv2_block1_1_conv (Conv2D)   (None, 64, 64, 64)   4160        ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block1_1_relu[0][0]']    
                                                                                                  
 conv2_block1_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_0_conv (Conv2D)   (None, 64, 64, 256)  16640       ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block1_2_relu[0][0]']    
                                                                                                  
 conv2_block1_0_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_0_bn[0][0]',      
                                                                  'conv2_block1_3_bn[0][0]']      
                                                                                                  
 conv2_block1_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block1_add[0][0]']       
                                                                                                  
 conv2_block2_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block1_out[0][0]']       
                                                                                                  
 conv2_block2_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block2_1_relu[0][0]']    
                                                                                                  
 conv2_block2_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block2_2_relu[0][0]']    
                                                                                                  
 conv2_block2_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_out[0][0]',       
                                                                  'conv2_block2_3_bn[0][0]']      
                                                                                                  
 conv2_block2_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block2_add[0][0]']       
                                                                                                  
 conv2_block3_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block2_out[0][0]']       
                                                                                                  
 conv2_block3_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block3_1_relu[0][0]']    
                                                                                                  
 conv2_block3_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block3_2_relu[0][0]']    
                                                                                                  
 conv2_block3_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_add (Add)         (None, 64, 64, 256)  0           ['conv2_block2_out[0][0]',       
                                                                  'conv2_block3_3_bn[0][0]']      
                                                                                                  
 conv2_block3_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block3_add[0][0]']       
                                                                                                  
 conv3_block1_1_conv (Conv2D)   (None, 32, 32, 128)  32896       ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block1_1_relu[0][0]']    
                                                                                                  
 conv3_block1_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_0_conv (Conv2D)   (None, 32, 32, 512)  131584      ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block1_2_relu[0][0]']    
                                                                                                  
 conv3_block1_0_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_0_bn[0][0]',      
                                                                  'conv3_block1_3_bn[0][0]']      
                                                                                                  
 conv3_block1_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block1_add[0][0]']       
                                                                                                  
 conv3_block2_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block1_out[0][0]']       
                                                                                                  
 conv3_block2_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block2_1_relu[0][0]']    
                                                                                                  
 conv3_block2_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block2_2_relu[0][0]']    
                                                                                                  
 conv3_block2_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_out[0][0]',       
                                                                  'conv3_block2_3_bn[0][0]']      
                                                                                                  
 conv3_block2_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block2_add[0][0]']       
                                                                                                  
 conv3_block3_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block2_out[0][0]']       
                                                                                                  
 conv3_block3_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block3_1_relu[0][0]']    
                                                                                                  
 conv3_block3_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block3_2_relu[0][0]']    
                                                                                                  
 conv3_block3_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_add (Add)         (None, 32, 32, 512)  0           ['conv3_block2_out[0][0]',       
                                                                  'conv3_block3_3_bn[0][0]']      
                                                                                                  
 conv3_block3_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block3_add[0][0]']       
                                                                                                  
 conv3_block4_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block3_out[0][0]']       
                                                                                                  
 conv3_block4_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block4_1_relu[0][0]']    
                                                                                                  
 conv3_block4_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block4_2_relu[0][0]']    
                                                                                                  
 conv3_block4_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block4_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_add (Add)         (None, 32, 32, 512)  0           ['conv3_block3_out[0][0]',       
                                                                  'conv3_block4_3_bn[0][0]']      
                                                                                                  
 conv3_block4_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block4_add[0][0]']       
                                                                                                  
 conv4_block1_1_conv (Conv2D)   (None, 16, 16, 256)  131328      ['conv3_block4_out[0][0]']       
                                                                                                  
 conv4_block1_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block1_1_relu[0][0]']    
                                                                                                  
 conv4_block1_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_0_conv (Conv2D)   (None, 16, 16, 1024  525312      ['conv3_block4_out[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block1_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block1_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block1_0_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_0_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_0_bn[0][0]',      
                                )                                 'conv4_block1_3_bn[0][0]']      
                                                                                                  
 conv4_block1_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block1_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block2_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block1_out[0][0]']       
                                                                                                  
 conv4_block2_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block2_1_relu[0][0]']    
                                                                                                  
 conv4_block2_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block2_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block2_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block2_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block2_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_out[0][0]',       
                                )                                 'conv4_block2_3_bn[0][0]']      
                                                                                                  
 conv4_block2_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block2_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block3_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block2_out[0][0]']       
                                                                                                  
 conv4_block3_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block3_1_relu[0][0]']    
                                                                                                  
 conv4_block3_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block3_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block3_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block3_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block3_add (Add)         (None, 16, 16, 1024  0           ['conv4_block2_out[0][0]',       
                                )                                 'conv4_block3_3_bn[0][0]']      
                                                                                                  
 conv4_block3_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block3_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block4_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block3_out[0][0]']       
                                                                                                  
 conv4_block4_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block4_1_relu[0][0]']    
                                                                                                  
 conv4_block4_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block4_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block4_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block4_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block4_add (Add)         (None, 16, 16, 1024  0           ['conv4_block3_out[0][0]',       
                                )                                 'conv4_block4_3_bn[0][0]']      
                                                                                                  
 conv4_block4_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block4_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block5_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block4_out[0][0]']       
                                                                                                  
 conv4_block5_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block5_1_relu[0][0]']    
                                                                                                  
 conv4_block5_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block5_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block5_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block5_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block5_add (Add)         (None, 16, 16, 1024  0           ['conv4_block4_out[0][0]',       
                                )                                 'conv4_block5_3_bn[0][0]']      
                                                                                                  
 conv4_block5_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block5_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block6_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block5_out[0][0]']       
                                                                                                  
 conv4_block6_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block6_1_relu[0][0]']    
                                                                                                  
 conv4_block6_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block6_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block6_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block6_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block6_add (Add)         (None, 16, 16, 1024  0           ['conv4_block5_out[0][0]',       
                                )                                 'conv4_block6_3_bn[0][0]']      
                                                                                                  
 conv4_block6_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block6_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv5_block1_1_conv (Conv2D)   (None, 8, 8, 512)    524800      ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block1_1_relu[0][0]']    
                                                                                                  
 conv5_block1_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_0_conv (Conv2D)   (None, 8, 8, 2048)   2099200     ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    
                                                                                                  
 conv5_block1_0_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_0_bn[0][0]',      
                                                                  'conv5_block1_3_bn[0][0]']      
                                                                                                  
 conv5_block1_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block1_add[0][0]']       
                                                                                                  
 conv5_block2_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block1_out[0][0]']       
                                                                                                  
 conv5_block2_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block2_1_relu[0][0]']    
                                                                                                  
 conv5_block2_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    
                                                                                                  
 conv5_block2_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_out[0][0]',       
                                                                  'conv5_block2_3_bn[0][0]']      
                                                                                                  
 conv5_block2_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block2_add[0][0]']       
                                                                                                  
 conv5_block3_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block2_out[0][0]']       
                                                                                                  
 conv5_block3_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block3_1_relu[0][0]']    
                                                                                                  
 conv5_block3_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    
                                                                                                  
 conv5_block3_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block2_out[0][0]',       
                                                                  'conv5_block3_3_bn[0][0]']      
                                                                                                  
 conv5_block3_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block3_add[0][0]']       
                                                                                                  
==================================================================================================
Total params: 23,587,712
Trainable params: 23,534,592
Non-trainable params: 53,120
__________________________________________________________________________________________________


# before this i tried with trainable layer but the accuracy was less as compared
for layer in clf_model.layers:
    layers.trainable = False


head = clf_model.output
head = AveragePooling2D(pool_size=(4,4))(head)
head = Flatten(name='Flatten')(head)
head = Dense(256, activation='relu')(head)
head = Dropout(0.3)(head)
head = Dense(256, activation='relu')(head)
head = Dropout(0.3)(head)
head = Dense(2, activation='softmax')(head)

model = Model(clf_model.input, head)
model.compile(loss = 'categorical_crossentropy', 
              optimizer='adam', 
              metrics= ["accuracy"]
             )
model.summary()

Model: "model"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_1 (InputLayer)           [(None, 256, 256, 3  0           []                               
                                )]                                                                
                                                                                                  
 conv1_pad (ZeroPadding2D)      (None, 262, 262, 3)  0           ['input_1[0][0]']                
                                                                                                  
 conv1_conv (Conv2D)            (None, 128, 128, 64  9472        ['conv1_pad[0][0]']              
                                )                                                                 
                                                                                                  
 conv1_bn (BatchNormalization)  (None, 128, 128, 64  256         ['conv1_conv[0][0]']             
                                )                                                                 
                                                                                                  
 conv1_relu (Activation)        (None, 128, 128, 64  0           ['conv1_bn[0][0]']               
                                )                                                                 
                                                                                                  
 pool1_pad (ZeroPadding2D)      (None, 130, 130, 64  0           ['conv1_relu[0][0]']             
                                )                                                                 
                                                                                                  
 pool1_pool (MaxPooling2D)      (None, 64, 64, 64)   0           ['pool1_pad[0][0]']              
                                                                                                  
 conv2_block1_1_conv (Conv2D)   (None, 64, 64, 64)   4160        ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block1_1_relu[0][0]']    
                                                                                                  
 conv2_block1_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_0_conv (Conv2D)   (None, 64, 64, 256)  16640       ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block1_2_relu[0][0]']    
                                                                                                  
 conv2_block1_0_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_0_bn[0][0]',      
                                                                  'conv2_block1_3_bn[0][0]']      
                                                                                                  
 conv2_block1_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block1_add[0][0]']       
                                                                                                  
 conv2_block2_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block1_out[0][0]']       
                                                                                                  
 conv2_block2_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block2_1_relu[0][0]']    
                                                                                                  
 conv2_block2_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block2_2_relu[0][0]']    
                                                                                                  
 conv2_block2_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_out[0][0]',       
                                                                  'conv2_block2_3_bn[0][0]']      
                                                                                                  
 conv2_block2_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block2_add[0][0]']       
                                                                                                  
 conv2_block3_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block2_out[0][0]']       
                                                                                                  
 conv2_block3_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block3_1_relu[0][0]']    
                                                                                                  
 conv2_block3_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block3_2_relu[0][0]']    
                                                                                                  
 conv2_block3_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_add (Add)         (None, 64, 64, 256)  0           ['conv2_block2_out[0][0]',       
                                                                  'conv2_block3_3_bn[0][0]']      
                                                                                                  
 conv2_block3_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block3_add[0][0]']       
                                                                                                  
 conv3_block1_1_conv (Conv2D)   (None, 32, 32, 128)  32896       ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block1_1_relu[0][0]']    
                                                                                                  
 conv3_block1_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_0_conv (Conv2D)   (None, 32, 32, 512)  131584      ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block1_2_relu[0][0]']    
                                                                                                  
 conv3_block1_0_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_0_bn[0][0]',      
                                                                  'conv3_block1_3_bn[0][0]']      
                                                                                                  
 conv3_block1_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block1_add[0][0]']       
                                                                                                  
 conv3_block2_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block1_out[0][0]']       
                                                                                                  
 conv3_block2_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block2_1_relu[0][0]']    
                                                                                                  
 conv3_block2_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block2_2_relu[0][0]']    
                                                                                                  
 conv3_block2_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_out[0][0]',       
                                                                  'conv3_block2_3_bn[0][0]']      
                                                                                                  
 conv3_block2_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block2_add[0][0]']       
                                                                                                  
 conv3_block3_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block2_out[0][0]']       
                                                                                                  
 conv3_block3_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block3_1_relu[0][0]']    
                                                                                                  
 conv3_block3_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block3_2_relu[0][0]']    
                                                                                                  
 conv3_block3_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_add (Add)         (None, 32, 32, 512)  0           ['conv3_block2_out[0][0]',       
                                                                  'conv3_block3_3_bn[0][0]']      
                                                                                                  
 conv3_block3_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block3_add[0][0]']       
                                                                                                  
 conv3_block4_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block3_out[0][0]']       
                                                                                                  
 conv3_block4_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block4_1_relu[0][0]']    
                                                                                                  
 conv3_block4_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block4_2_relu[0][0]']    
                                                                                                  
 conv3_block4_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block4_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_add (Add)         (None, 32, 32, 512)  0           ['conv3_block3_out[0][0]',       
                                                                  'conv3_block4_3_bn[0][0]']      
                                                                                                  
 conv3_block4_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block4_add[0][0]']       
                                                                                                  
 conv4_block1_1_conv (Conv2D)   (None, 16, 16, 256)  131328      ['conv3_block4_out[0][0]']       
                                                                                                  
 conv4_block1_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block1_1_relu[0][0]']    
                                                                                                  
 conv4_block1_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_0_conv (Conv2D)   (None, 16, 16, 1024  525312      ['conv3_block4_out[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block1_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block1_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block1_0_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_0_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_0_bn[0][0]',      
                                )                                 'conv4_block1_3_bn[0][0]']      
                                                                                                  
 conv4_block1_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block1_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block2_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block1_out[0][0]']       
                                                                                                  
 conv4_block2_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block2_1_relu[0][0]']    
                                                                                                  
 conv4_block2_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block2_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block2_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block2_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block2_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_out[0][0]',       
                                )                                 'conv4_block2_3_bn[0][0]']      
                                                                                                  
 conv4_block2_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block2_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block3_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block2_out[0][0]']       
                                                                                                  
 conv4_block3_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block3_1_relu[0][0]']    
                                                                                                  
 conv4_block3_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block3_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block3_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block3_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block3_add (Add)         (None, 16, 16, 1024  0           ['conv4_block2_out[0][0]',       
                                )                                 'conv4_block3_3_bn[0][0]']      
                                                                                                  
 conv4_block3_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block3_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block4_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block3_out[0][0]']       
                                                                                                  
 conv4_block4_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block4_1_relu[0][0]']    
                                                                                                  
 conv4_block4_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block4_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block4_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block4_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block4_add (Add)         (None, 16, 16, 1024  0           ['conv4_block3_out[0][0]',       
                                )                                 'conv4_block4_3_bn[0][0]']      
                                                                                                  
 conv4_block4_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block4_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block5_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block4_out[0][0]']       
                                                                                                  
 conv4_block5_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block5_1_relu[0][0]']    
                                                                                                  
 conv4_block5_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block5_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block5_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block5_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block5_add (Add)         (None, 16, 16, 1024  0           ['conv4_block4_out[0][0]',       
                                )                                 'conv4_block5_3_bn[0][0]']      
                                                                                                  
 conv4_block5_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block5_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block6_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block5_out[0][0]']       
                                                                                                  
 conv4_block6_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block6_1_relu[0][0]']    
                                                                                                  
 conv4_block6_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block6_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block6_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block6_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block6_add (Add)         (None, 16, 16, 1024  0           ['conv4_block5_out[0][0]',       
                                )                                 'conv4_block6_3_bn[0][0]']      
                                                                                                  
 conv4_block6_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block6_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv5_block1_1_conv (Conv2D)   (None, 8, 8, 512)    524800      ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block1_1_relu[0][0]']    
                                                                                                  
 conv5_block1_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_0_conv (Conv2D)   (None, 8, 8, 2048)   2099200     ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    
                                                                                                  
 conv5_block1_0_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_0_bn[0][0]',      
                                                                  'conv5_block1_3_bn[0][0]']      
                                                                                                  
 conv5_block1_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block1_add[0][0]']       
                                                                                                  
 conv5_block2_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block1_out[0][0]']       
                                                                                                  
 conv5_block2_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block2_1_relu[0][0]']    
                                                                                                  
 conv5_block2_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    
                                                                                                  
 conv5_block2_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_out[0][0]',       
                                                                  'conv5_block2_3_bn[0][0]']      
                                                                                                  
 conv5_block2_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block2_add[0][0]']       
                                                                                                  
 conv5_block3_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block2_out[0][0]']       
                                                                                                  
 conv5_block3_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block3_1_relu[0][0]']    
                                                                                                  
 conv5_block3_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    
                                                                                                  
 conv5_block3_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block2_out[0][0]',       
                                                                  'conv5_block3_3_bn[0][0]']      
                                                                                                  
 conv5_block3_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block3_add[0][0]']       
                                                                                                  
 average_pooling2d (AveragePool  (None, 2, 2, 2048)  0           ['conv5_block3_out[0][0]']       
 ing2D)                                                                                           
                                                                                                  
 Flatten (Flatten)              (None, 8192)         0           ['average_pooling2d[0][0]']      
                                                                                                  
 dense (Dense)                  (None, 256)          2097408     ['Flatten[0][0]']                
                                                                                                  
 dropout (Dropout)              (None, 256)          0           ['dense[0][0]']                  
                                                                                                  
 dense_1 (Dense)                (None, 256)          65792       ['dropout[0][0]']                
                                                                                                  
 dropout_1 (Dropout)            (None, 256)          0           ['dense_1[0][0]']                
                                                                                                  
 dense_2 (Dense)                (None, 2)            514         ['dropout_1[0][0]']              
                                                                                                  
==================================================================================================
Total params: 25,751,426
Trainable params: 25,698,306
Non-trainable params: 53,120
__________________________________________________________________________________________________


earlystopping = EarlyStopping(monitor='val_loss', 
                              mode='min', 
                              verbose=1, 
                              patience=15
                             )
checkpointer = ModelCheckpoint(filepath="clf-resnet-weights.hdf5", 
                               verbose=1, 
                               save_best_only=True
                              )
reduce_lr = ReduceLROnPlateau(monitor='val_loss',
                              mode='min',
                              verbose=1,
                              patience=10,
                              min_delta=0.0001,
                              factor=0.2
                             )
callbacks = [checkpointer, earlystopping, reduce_lr]


h = model.fit(train_generator, 
              steps_per_epoch= train_generator.n // train_generator.batch_size, 
              epochs = 50, 
              validation_data= valid_generator, 
              validation_steps= valid_generator.n // valid_generator.batch_size, 
              callbacks=[checkpointer, earlystopping])


# saving model achitecture in json file
model_json = model.to_json()
with open("clf-resnet-model.json", "w") as json_file:
    json_file.write(model_json)


h.history.keys()


plt.figure(figsize=(12,5))
plt.subplot(1,2,1)
plt.plot(h.history['loss']);
plt.plot(h.history['val_loss']);
plt.title("Classification Model LOSS");
plt.ylabel("loss");
plt.xlabel("Epochs");
plt.legend(['train', 'val']);

plt.subplot(1,2,2)
plt.plot(h.history['accuracy']);
plt.plot(h.history['val_accuracy']);
plt.title("Classification Model Acc");
plt.ylabel("Accuracy");
plt.xlabel("Epochs");
plt.legend(['train', 'val']);


_, acc = model.evaluate(test_generator)
print("Test accuracy : {} %".format(acc*100))


prediction = model.predict(test_generator)

pred = np.argmax(prediction, axis=1)
#pred = np.asarray(pred).astype('str')
original = np.asarray(test['mask']).astype('int')

from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
accuracy = accuracy_score(original, pred)
print(accuracy)

cm = confusion_matrix(original, pred)

report = classification_report(original, pred, labels = [0,1])
print(report)
plt.figure(figsize = (5,5))
sns.heatmap(cm, annot=True);


brain_df_mask = brain_df[brain_df['mask'] == 1]


brain_df_mask.shape

(1373, 4)


# creating test, train and val sets
X_train, X_val = train_test_split(brain_df_mask, test_size=0.15)
X_test, X_val = train_test_split(X_val, test_size=0.5)
print("Train size is {}, valid size is {} & test size is {}".format(len(X_train), len(X_val), len(X_test)))

train_ids = list(X_train.image_path)
train_mask = list(X_train.mask_path)

val_ids = list(X_val.image_path)
val_mask= list(X_val.mask_path)

Train size is 1167, valid size is 103 & test size is 103


class DataGenerator(tf.keras.utils.Sequence):
  def __init__(self, ids , mask, image_dir = './', batch_size = 16, img_h = 256, img_w = 256, shuffle = True):

    self.ids = ids
    self.mask = mask
    self.image_dir = image_dir
    self.batch_size = batch_size
    self.img_h = img_h
    self.img_w = img_w
    self.shuffle = shuffle
    self.on_epoch_end()

  def __len__(self):
    'Get the number of batches per epoch'

    return int(np.floor(len(self.ids)) / self.batch_size)

  def __getitem__(self, index):
    'Generate a batch of data'

    #generate index of batch_size length
    indexes = self.indexes[index* self.batch_size : (index+1) * self.batch_size]

    #get the ImageId corresponding to the indexes created above based on batch size
    list_ids = [self.ids[i] for i in indexes]

    #get the MaskId corresponding to the indexes created above based on batch size
    list_mask = [self.mask[i] for i in indexes]


    #generate data for the X(features) and y(label)
    X, y = self.__data_generation(list_ids, list_mask)

    #returning the data
    return X, y

  def on_epoch_end(self):
    'Used for updating the indices after each epoch, once at the beginning as well as at the end of each epoch'
    
    #getting the array of indices based on the input dataframe
    self.indexes = np.arange(len(self.ids))

    #if shuffle is true, shuffle the indices
    if self.shuffle:
      np.random.shuffle(self.indexes)

  def __data_generation(self, list_ids, list_mask):
    'generate the data corresponding the indexes in a given batch of images'

    # create empty arrays of shape (batch_size,height,width,depth) 
    #Depth is 3 for input and depth is taken as 1 for output becasue mask consist only of 1 channel.
    X = np.empty((self.batch_size, self.img_h, self.img_w, 3))
    y = np.empty((self.batch_size, self.img_h, self.img_w, 1))

    #iterate through the dataframe rows, whose size is equal to the batch_size
    for i in range(len(list_ids)):
      #path of the image
      img_path = str(list_ids[i])
      
      #mask path
      mask_path = str(list_mask[i])
      
      #reading the original image and the corresponding mask image
      img = io.imread(img_path)
      mask = io.imread(mask_path)

      #resizing and coverting them to array of type float64
      img = cv2.resize(img,(self.img_h,self.img_w))
      img = np.array(img, dtype = np.float64)
      
      mask = cv2.resize(mask,(self.img_h,self.img_w))
      mask = np.array(mask, dtype = np.float64)

      #standardising 
      img -= img.mean()
      img /= img.std()
      
      mask -= mask.mean()
      mask /= mask.std()
      
      #Adding image to the empty array
      X[i,] = img
      
      #expanding the dimnesion of the image from (256,256) to (256,256,1)
      y[i,] = np.expand_dims(mask, axis = 2)
    
    #normalizing y
    y = (y > 0).astype(int)

    return X, y

train_data = DataGenerator(train_ids, train_mask)
val_data = DataGenerator(val_ids, val_mask)


# lets create model now
def resblock(X, f):
    '''
    function for creating res block
    '''
    X_copy = X  #copy of input
    
    # main path
    X = Conv2D(f, kernel_size=(1,1), kernel_initializer='he_normal')(X)
    X = BatchNormalization()(X)
    X = Activation('relu')(X)
    
    X = Conv2D(f, kernel_size=(3,3), padding='same', kernel_initializer='he_normal')(X)
    X = BatchNormalization()(X)
    
    # shortcut path
    X_copy = Conv2D(f, kernel_size=(1,1), kernel_initializer='he_normal')(X_copy)
    X_copy = BatchNormalization()(X_copy)
    
    # Adding the output from main path and short path together
    X = Add()([X, X_copy])
    X = Activation('relu')(X)
    
    return X

def upsample_concat(x, skip):
    '''
    funtion for upsampling image
    '''
    X = UpSampling2D((2,2))(x)
    merge = Concatenate()([X, skip])
    
    return merge


input_shape = (256,256,3)
X_input = Input(input_shape) #iniating tensor of input shape

# Stage 1
conv_1 = Conv2D(16, 3, activation='relu', padding='same', kernel_initializer='he_normal')(X_input)
conv_1 = BatchNormalization()(conv_1)
conv_1 = Conv2D(16, 3, activation='relu', padding='same', kernel_initializer='he_normal')(conv_1)
conv_1 = BatchNormalization()(conv_1)
pool_1 = MaxPool2D((2,2))(conv_1)

# stage 2
conv_2 = resblock(pool_1, 32)
pool_2 = MaxPool2D((2,2))(conv_2)

# Stage 3
conv_3 = resblock(pool_2, 64)
pool_3 = MaxPool2D((2,2))(conv_3)

# Stage 4
conv_4 = resblock(pool_3, 128)
pool_4 = MaxPool2D((2,2))(conv_4)

# Stage 5 (bottle neck)
conv_5 = resblock(pool_4, 256)

# Upsample Stage 1
up_1 = upsample_concat(conv_5, conv_4)
up_1 = resblock(up_1, 128)

# Upsample Stage 2
up_2 = upsample_concat(up_1, conv_3)
up_2 = resblock(up_2, 64)

# Upsample Stage 3
up_3 = upsample_concat(up_2, conv_2)
up_3 = resblock(up_3, 32)

# Upsample Stage 4
up_4 = upsample_concat(up_3, conv_1)
up_4 = resblock(up_4, 16)

# final output
out = Conv2D(1, (1,1), kernel_initializer='he_normal', padding='same', activation='sigmoid')(up_4)

seg_model = Model(X_input, out)
seg_model.summary()

Model: "model_1"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_2 (InputLayer)           [(None, 256, 256, 3  0           []                               
                                )]                                                                
                                                                                                  
 conv2d (Conv2D)                (None, 256, 256, 16  448         ['input_2[0][0]']                
                                )                                                                 
                                                                                                  
 batch_normalization (BatchNorm  (None, 256, 256, 16  64         ['conv2d[0][0]']                 
 alization)                     )                                                                 
                                                                                                  
 conv2d_1 (Conv2D)              (None, 256, 256, 16  2320        ['batch_normalization[0][0]']    
                                )                                                                 
                                                                                                  
 batch_normalization_1 (BatchNo  (None, 256, 256, 16  64         ['conv2d_1[0][0]']               
 rmalization)                   )                                                                 
                                                                                                  
 max_pooling2d (MaxPooling2D)   (None, 128, 128, 16  0           ['batch_normalization_1[0][0]']  
                                )                                                                 
                                                                                                  
 conv2d_2 (Conv2D)              (None, 128, 128, 32  544         ['max_pooling2d[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_2 (BatchNo  (None, 128, 128, 32  128        ['conv2d_2[0][0]']               
 rmalization)                   )                                                                 
                                                                                                  
 activation (Activation)        (None, 128, 128, 32  0           ['batch_normalization_2[0][0]']  
                                )                                                                 
                                                                                                  
 conv2d_3 (Conv2D)              (None, 128, 128, 32  9248        ['activation[0][0]']             
                                )                                                                 
                                                                                                  
 conv2d_4 (Conv2D)              (None, 128, 128, 32  544         ['max_pooling2d[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_3 (BatchNo  (None, 128, 128, 32  128        ['conv2d_3[0][0]']               
 rmalization)                   )                                                                 
                                                                                                  
 batch_normalization_4 (BatchNo  (None, 128, 128, 32  128        ['conv2d_4[0][0]']               
 rmalization)                   )                                                                 
                                                                                                  
 add (Add)                      (None, 128, 128, 32  0           ['batch_normalization_3[0][0]',  
                                )                                 'batch_normalization_4[0][0]']  
                                                                                                  
 activation_1 (Activation)      (None, 128, 128, 32  0           ['add[0][0]']                    
                                )                                                                 
                                                                                                  
 max_pooling2d_1 (MaxPooling2D)  (None, 64, 64, 32)  0           ['activation_1[0][0]']           
                                                                                                  
 conv2d_5 (Conv2D)              (None, 64, 64, 64)   2112        ['max_pooling2d_1[0][0]']        
                                                                                                  
 batch_normalization_5 (BatchNo  (None, 64, 64, 64)  256         ['conv2d_5[0][0]']               
 rmalization)                                                                                     
                                                                                                  
 activation_2 (Activation)      (None, 64, 64, 64)   0           ['batch_normalization_5[0][0]']  
                                                                                                  
 conv2d_6 (Conv2D)              (None, 64, 64, 64)   36928       ['activation_2[0][0]']           
                                                                                                  
 conv2d_7 (Conv2D)              (None, 64, 64, 64)   2112        ['max_pooling2d_1[0][0]']        
                                                                                                  
 batch_normalization_6 (BatchNo  (None, 64, 64, 64)  256         ['conv2d_6[0][0]']               
 rmalization)                                                                                     
                                                                                                  
 batch_normalization_7 (BatchNo  (None, 64, 64, 64)  256         ['conv2d_7[0][0]']               
 rmalization)                                                                                     
                                                                                                  
 add_1 (Add)                    (None, 64, 64, 64)   0           ['batch_normalization_6[0][0]',  
                                                                  'batch_normalization_7[0][0]']  
                                                                                                  
 activation_3 (Activation)      (None, 64, 64, 64)   0           ['add_1[0][0]']                  
                                                                                                  
 max_pooling2d_2 (MaxPooling2D)  (None, 32, 32, 64)  0           ['activation_3[0][0]']           
                                                                                                  
 conv2d_8 (Conv2D)              (None, 32, 32, 128)  8320        ['max_pooling2d_2[0][0]']        
                                                                                                  
 batch_normalization_8 (BatchNo  (None, 32, 32, 128)  512        ['conv2d_8[0][0]']               
 rmalization)                                                                                     
                                                                                                  
 activation_4 (Activation)      (None, 32, 32, 128)  0           ['batch_normalization_8[0][0]']  
                                                                                                  
 conv2d_9 (Conv2D)              (None, 32, 32, 128)  147584      ['activation_4[0][0]']           
                                                                                                  
 conv2d_10 (Conv2D)             (None, 32, 32, 128)  8320        ['max_pooling2d_2[0][0]']        
                                                                                                  
 batch_normalization_9 (BatchNo  (None, 32, 32, 128)  512        ['conv2d_9[0][0]']               
 rmalization)                                                                                     
                                                                                                  
 batch_normalization_10 (BatchN  (None, 32, 32, 128)  512        ['conv2d_10[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 add_2 (Add)                    (None, 32, 32, 128)  0           ['batch_normalization_9[0][0]',  
                                                                  'batch_normalization_10[0][0]'] 
                                                                                                  
 activation_5 (Activation)      (None, 32, 32, 128)  0           ['add_2[0][0]']                  
                                                                                                  
 max_pooling2d_3 (MaxPooling2D)  (None, 16, 16, 128)  0          ['activation_5[0][0]']           
                                                                                                  
 conv2d_11 (Conv2D)             (None, 16, 16, 256)  33024       ['max_pooling2d_3[0][0]']        
                                                                                                  
 batch_normalization_11 (BatchN  (None, 16, 16, 256)  1024       ['conv2d_11[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 activation_6 (Activation)      (None, 16, 16, 256)  0           ['batch_normalization_11[0][0]'] 
                                                                                                  
 conv2d_12 (Conv2D)             (None, 16, 16, 256)  590080      ['activation_6[0][0]']           
                                                                                                  
 conv2d_13 (Conv2D)             (None, 16, 16, 256)  33024       ['max_pooling2d_3[0][0]']        
                                                                                                  
 batch_normalization_12 (BatchN  (None, 16, 16, 256)  1024       ['conv2d_12[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 batch_normalization_13 (BatchN  (None, 16, 16, 256)  1024       ['conv2d_13[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 add_3 (Add)                    (None, 16, 16, 256)  0           ['batch_normalization_12[0][0]', 
                                                                  'batch_normalization_13[0][0]'] 
                                                                                                  
 activation_7 (Activation)      (None, 16, 16, 256)  0           ['add_3[0][0]']                  
                                                                                                  
 up_sampling2d (UpSampling2D)   (None, 32, 32, 256)  0           ['activation_7[0][0]']           
                                                                                                  
 concatenate (Concatenate)      (None, 32, 32, 384)  0           ['up_sampling2d[0][0]',          
                                                                  'activation_5[0][0]']           
                                                                                                  
 conv2d_14 (Conv2D)             (None, 32, 32, 128)  49280       ['concatenate[0][0]']            
                                                                                                  
 batch_normalization_14 (BatchN  (None, 32, 32, 128)  512        ['conv2d_14[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 activation_8 (Activation)      (None, 32, 32, 128)  0           ['batch_normalization_14[0][0]'] 
                                                                                                  
 conv2d_15 (Conv2D)             (None, 32, 32, 128)  147584      ['activation_8[0][0]']           
                                                                                                  
 conv2d_16 (Conv2D)             (None, 32, 32, 128)  49280       ['concatenate[0][0]']            
                                                                                                  
 batch_normalization_15 (BatchN  (None, 32, 32, 128)  512        ['conv2d_15[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 batch_normalization_16 (BatchN  (None, 32, 32, 128)  512        ['conv2d_16[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 add_4 (Add)                    (None, 32, 32, 128)  0           ['batch_normalization_15[0][0]', 
                                                                  'batch_normalization_16[0][0]'] 
                                                                                                  
 activation_9 (Activation)      (None, 32, 32, 128)  0           ['add_4[0][0]']                  
                                                                                                  
 up_sampling2d_1 (UpSampling2D)  (None, 64, 64, 128)  0          ['activation_9[0][0]']           
                                                                                                  
 concatenate_1 (Concatenate)    (None, 64, 64, 192)  0           ['up_sampling2d_1[0][0]',        
                                                                  'activation_3[0][0]']           
                                                                                                  
 conv2d_17 (Conv2D)             (None, 64, 64, 64)   12352       ['concatenate_1[0][0]']          
                                                                                                  
 batch_normalization_17 (BatchN  (None, 64, 64, 64)  256         ['conv2d_17[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 activation_10 (Activation)     (None, 64, 64, 64)   0           ['batch_normalization_17[0][0]'] 
                                                                                                  
 conv2d_18 (Conv2D)             (None, 64, 64, 64)   36928       ['activation_10[0][0]']          
                                                                                                  
 conv2d_19 (Conv2D)             (None, 64, 64, 64)   12352       ['concatenate_1[0][0]']          
                                                                                                  
 batch_normalization_18 (BatchN  (None, 64, 64, 64)  256         ['conv2d_18[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 batch_normalization_19 (BatchN  (None, 64, 64, 64)  256         ['conv2d_19[0][0]']              
 ormalization)                                                                                    
                                                                                                  
 add_5 (Add)                    (None, 64, 64, 64)   0           ['batch_normalization_18[0][0]', 
                                                                  'batch_normalization_19[0][0]'] 
                                                                                                  
 activation_11 (Activation)     (None, 64, 64, 64)   0           ['add_5[0][0]']                  
                                                                                                  
 up_sampling2d_2 (UpSampling2D)  (None, 128, 128, 64  0          ['activation_11[0][0]']          
                                )                                                                 
                                                                                                  
 concatenate_2 (Concatenate)    (None, 128, 128, 96  0           ['up_sampling2d_2[0][0]',        
                                )                                 'activation_1[0][0]']           
                                                                                                  
 conv2d_20 (Conv2D)             (None, 128, 128, 32  3104        ['concatenate_2[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_20 (BatchN  (None, 128, 128, 32  128        ['conv2d_20[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 activation_12 (Activation)     (None, 128, 128, 32  0           ['batch_normalization_20[0][0]'] 
                                )                                                                 
                                                                                                  
 conv2d_21 (Conv2D)             (None, 128, 128, 32  9248        ['activation_12[0][0]']          
                                )                                                                 
                                                                                                  
 conv2d_22 (Conv2D)             (None, 128, 128, 32  3104        ['concatenate_2[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_21 (BatchN  (None, 128, 128, 32  128        ['conv2d_21[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 batch_normalization_22 (BatchN  (None, 128, 128, 32  128        ['conv2d_22[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 add_6 (Add)                    (None, 128, 128, 32  0           ['batch_normalization_21[0][0]', 
                                )                                 'batch_normalization_22[0][0]'] 
                                                                                                  
 activation_13 (Activation)     (None, 128, 128, 32  0           ['add_6[0][0]']                  
                                )                                                                 
                                                                                                  
 up_sampling2d_3 (UpSampling2D)  (None, 256, 256, 32  0          ['activation_13[0][0]']          
                                )                                                                 
                                                                                                  
 concatenate_3 (Concatenate)    (None, 256, 256, 48  0           ['up_sampling2d_3[0][0]',        
                                )                                 'batch_normalization_1[0][0]']  
                                                                                                  
 conv2d_23 (Conv2D)             (None, 256, 256, 16  784         ['concatenate_3[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_23 (BatchN  (None, 256, 256, 16  64         ['conv2d_23[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 activation_14 (Activation)     (None, 256, 256, 16  0           ['batch_normalization_23[0][0]'] 
                                )                                                                 
                                                                                                  
 conv2d_24 (Conv2D)             (None, 256, 256, 16  2320        ['activation_14[0][0]']          
                                )                                                                 
                                                                                                  
 conv2d_25 (Conv2D)             (None, 256, 256, 16  784         ['concatenate_3[0][0]']          
                                )                                                                 
                                                                                                  
 batch_normalization_24 (BatchN  (None, 256, 256, 16  64         ['conv2d_24[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 batch_normalization_25 (BatchN  (None, 256, 256, 16  64         ['conv2d_25[0][0]']              
 ormalization)                  )                                                                 
                                                                                                  
 add_7 (Add)                    (None, 256, 256, 16  0           ['batch_normalization_24[0][0]', 
                                )                                 'batch_normalization_25[0][0]'] 
                                                                                                  
 activation_15 (Activation)     (None, 256, 256, 16  0           ['add_7[0][0]']                  
                                )                                                                 
                                                                                                  
 conv2d_26 (Conv2D)             (None, 256, 256, 1)  17          ['activation_15[0][0]']          
                                                                                                  
==================================================================================================
Total params: 1,210,513
Trainable params: 1,206,129
Non-trainable params: 4,384
__________________________________________________________________________________________________


from keras.losses import binary_crossentropy

epsilon = 1e-5
smooth = 1

def tversky(y_true, y_pred):
    y_true_pos = K.flatten(y_true)
    y_pred_pos = K.flatten(y_pred)
    true_pos = K.sum(y_true_pos * y_pred_pos)
    false_neg = K.sum(y_true_pos * (1-y_pred_pos))
    false_pos = K.sum((1-y_true_pos)*y_pred_pos)
    alpha = 0.7
    return (true_pos + smooth)/(true_pos + alpha*false_neg + (1-alpha)*false_pos + smooth)

def focal_tversky(y_true,y_pred):
    y_true = tf.cast(y_true, tf.float32)
    y_pred = tf.cast(y_pred, tf.float32)
    
    pt_1 = tversky(y_true, y_pred)
    gamma = 0.75
    return K.pow((1-pt_1), gamma)

def tversky_loss(y_true, y_pred):
    return 1 - tversky(y_true,y_pred)


# compling model and callbacks functions
adam = tf.keras.optimizers.Adam(lr = 0.05, epsilon = 0.1)
seg_model.compile(optimizer = adam, 
                  loss = focal_tversky, 
                  metrics = [tversky]
                 )
#callbacks
earlystopping = EarlyStopping(monitor='val_loss',
                              mode='min', 
                              verbose=1, 
                              patience=20
                             )
# save the best model with lower validation loss
checkpointer = ModelCheckpoint(filepath="ResUNet-segModel-weights.hdf5", 
                               verbose=1, 
                               save_best_only=True
                              )
reduce_lr = ReduceLROnPlateau(monitor='val_loss',
                              mode='min',
                              verbose=1,
                              patience=10,
                              min_delta=0.0001,
                              factor=0.2
                             )

C:\Users\will.pratt\Documents\temp\lib\site-packages\keras\optimizer_v2\adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.
  super(Adam, self).__init__(name, **kwargs)


h = seg_model.fit(train_data, 
                  epochs = 60, 
                  validation_data = val_data,
                  callbacks = [checkpointer, earlystopping, reduce_lr]
                 )

Epoch 1/60
72/72 [==============================] - ETA: 0s - loss: 0.8465 - tversky: 0.1981
Epoch 00001: val_loss improved from inf to 0.80569, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 213s 3s/step - loss: 0.8465 - tversky: 0.1981 - val_loss: 0.8057 - val_tversky: 0.2502 - lr: 0.0500

C:\Users\will.pratt\Documents\temp\lib\site-packages\keras\engine\functional.py:1410: CustomMaskWarning: Custom mask layers require a config and must override get_config. When loading, the custom mask layer must be passed to the custom_objects argument.
  layer_config = serialize_layer_fn(layer)

Epoch 2/60
72/72 [==============================] - ETA: 0s - loss: 0.5110 - tversky: 0.5868
Epoch 00002: val_loss improved from 0.80569 to 0.67348, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 203s 3s/step - loss: 0.5110 - tversky: 0.5868 - val_loss: 0.6735 - val_tversky: 0.4096 - lr: 0.0500
Epoch 3/60
72/72 [==============================] - ETA: 0s - loss: 0.3790 - tversky: 0.7232
Epoch 00003: val_loss improved from 0.67348 to 0.56456, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 212s 3s/step - loss: 0.3790 - tversky: 0.7232 - val_loss: 0.5646 - val_tversky: 0.5327 - lr: 0.0500
Epoch 4/60
72/72 [==============================] - ETA: 0s - loss: 0.3321 - tversky: 0.7681
Epoch 00004: val_loss improved from 0.56456 to 0.48963, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 217s 3s/step - loss: 0.3321 - tversky: 0.7681 - val_loss: 0.4896 - val_tversky: 0.6131 - lr: 0.0500
Epoch 5/60
72/72 [==============================] - ETA: 0s - loss: 0.2940 - tversky: 0.8026
Epoch 00005: val_loss improved from 0.48963 to 0.30965, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 207s 3s/step - loss: 0.2940 - tversky: 0.8026 - val_loss: 0.3096 - val_tversky: 0.7899 - lr: 0.0500
Epoch 6/60
72/72 [==============================] - ETA: 0s - loss: 0.2744 - tversky: 0.8198
Epoch 00006: val_loss did not improve from 0.30965
72/72 [==============================] - 205s 3s/step - loss: 0.2744 - tversky: 0.8198 - val_loss: 0.3544 - val_tversky: 0.7489 - lr: 0.0500
Epoch 7/60
72/72 [==============================] - ETA: 0s - loss: 0.2622 - tversky: 0.8308
Epoch 00007: val_loss improved from 0.30965 to 0.26843, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 206s 3s/step - loss: 0.2622 - tversky: 0.8308 - val_loss: 0.2684 - val_tversky: 0.8241 - lr: 0.0500
Epoch 8/60
72/72 [==============================] - ETA: 0s - loss: 0.2349 - tversky: 0.8541
Epoch 00008: val_loss did not improve from 0.26843
72/72 [==============================] - 210s 3s/step - loss: 0.2349 - tversky: 0.8541 - val_loss: 0.2881 - val_tversky: 0.8084 - lr: 0.0500
Epoch 9/60
72/72 [==============================] - ETA: 0s - loss: 0.2205 - tversky: 0.8657
Epoch 00009: val_loss improved from 0.26843 to 0.25063, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 215s 3s/step - loss: 0.2205 - tversky: 0.8657 - val_loss: 0.2506 - val_tversky: 0.8411 - lr: 0.0500
Epoch 10/60
72/72 [==============================] - ETA: 0s - loss: 0.2102 - tversky: 0.8743
Epoch 00010: val_loss improved from 0.25063 to 0.23099, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 210s 3s/step - loss: 0.2102 - tversky: 0.8743 - val_loss: 0.2310 - val_tversky: 0.8577 - lr: 0.0500
Epoch 11/60
72/72 [==============================] - ETA: 0s - loss: 0.2040 - tversky: 0.8788
Epoch 00011: val_loss did not improve from 0.23099
72/72 [==============================] - 209s 3s/step - loss: 0.2040 - tversky: 0.8788 - val_loss: 0.2318 - val_tversky: 0.8566 - lr: 0.0500
Epoch 12/60
72/72 [==============================] - ETA: 0s - loss: 0.1938 - tversky: 0.8868
Epoch 00012: val_loss did not improve from 0.23099
72/72 [==============================] - 209s 3s/step - loss: 0.1938 - tversky: 0.8868 - val_loss: 0.2992 - val_tversky: 0.7960 - lr: 0.0500
Epoch 13/60
72/72 [==============================] - ETA: 0s - loss: 0.1877 - tversky: 0.8919
Epoch 00013: val_loss improved from 0.23099 to 0.21617, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 204s 3s/step - loss: 0.1877 - tversky: 0.8919 - val_loss: 0.2162 - val_tversky: 0.8697 - lr: 0.0500
Epoch 14/60
72/72 [==============================] - ETA: 0s - loss: 0.1886 - tversky: 0.8910
Epoch 00014: val_loss did not improve from 0.21617
72/72 [==============================] - 204s 3s/step - loss: 0.1886 - tversky: 0.8910 - val_loss: 0.2312 - val_tversky: 0.8569 - lr: 0.0500
Epoch 15/60
72/72 [==============================] - ETA: 0s - loss: 0.1698 - tversky: 0.9054
Epoch 00015: val_loss improved from 0.21617 to 0.19208, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 205s 3s/step - loss: 0.1698 - tversky: 0.9054 - val_loss: 0.1921 - val_tversky: 0.8888 - lr: 0.0500
Epoch 16/60
72/72 [==============================] - ETA: 0s - loss: 0.1683 - tversky: 0.9064
Epoch 00016: val_loss improved from 0.19208 to 0.18824, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 207s 3s/step - loss: 0.1683 - tversky: 0.9064 - val_loss: 0.1882 - val_tversky: 0.8914 - lr: 0.0500
Epoch 17/60
72/72 [==============================] - ETA: 0s - loss: 0.1581 - tversky: 0.9140
Epoch 00017: val_loss did not improve from 0.18824
72/72 [==============================] - 207s 3s/step - loss: 0.1581 - tversky: 0.9140 - val_loss: 0.2038 - val_tversky: 0.8795 - lr: 0.0500
Epoch 18/60
72/72 [==============================] - ETA: 0s - loss: 0.1530 - tversky: 0.9177
Epoch 00018: val_loss improved from 0.18824 to 0.18632, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 208s 3s/step - loss: 0.1530 - tversky: 0.9177 - val_loss: 0.1863 - val_tversky: 0.8930 - lr: 0.0500
Epoch 19/60
72/72 [==============================] - ETA: 0s - loss: 0.1497 - tversky: 0.9201
Epoch 00019: val_loss improved from 0.18632 to 0.18138, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 206s 3s/step - loss: 0.1497 - tversky: 0.9201 - val_loss: 0.1814 - val_tversky: 0.8972 - lr: 0.0500
Epoch 20/60
72/72 [==============================] - ETA: 0s - loss: 0.1493 - tversky: 0.9204
Epoch 00020: val_loss improved from 0.18138 to 0.17366, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 205s 3s/step - loss: 0.1493 - tversky: 0.9204 - val_loss: 0.1737 - val_tversky: 0.9029 - lr: 0.0500
Epoch 21/60
72/72 [==============================] - ETA: 0s - loss: 0.1434 - tversky: 0.9245
Epoch 00021: val_loss did not improve from 0.17366
72/72 [==============================] - 206s 3s/step - loss: 0.1434 - tversky: 0.9245 - val_loss: 0.1925 - val_tversky: 0.8880 - lr: 0.0500
Epoch 22/60
72/72 [==============================] - ETA: 0s - loss: 0.1457 - tversky: 0.9228
Epoch 00022: val_loss did not improve from 0.17366
72/72 [==============================] - 206s 3s/step - loss: 0.1457 - tversky: 0.9228 - val_loss: 0.1815 - val_tversky: 0.8968 - lr: 0.0500
Epoch 23/60
72/72 [==============================] - ETA: 0s - loss: 0.1394 - tversky: 0.9273
Epoch 00023: val_loss did not improve from 0.17366
72/72 [==============================] - 206s 3s/step - loss: 0.1394 - tversky: 0.9273 - val_loss: 0.1854 - val_tversky: 0.8938 - lr: 0.0500
Epoch 24/60
72/72 [==============================] - ETA: 0s - loss: 0.1321 - tversky: 0.9324
Epoch 00024: val_loss improved from 0.17366 to 0.16542, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 204s 3s/step - loss: 0.1321 - tversky: 0.9324 - val_loss: 0.1654 - val_tversky: 0.9088 - lr: 0.0500
Epoch 25/60
72/72 [==============================] - ETA: 0s - loss: 0.1273 - tversky: 0.9357
Epoch 00025: val_loss did not improve from 0.16542
72/72 [==============================] - 205s 3s/step - loss: 0.1273 - tversky: 0.9357 - val_loss: 0.1728 - val_tversky: 0.9036 - lr: 0.0500
Epoch 26/60
72/72 [==============================] - ETA: 0s - loss: 0.1250 - tversky: 0.9373
Epoch 00026: val_loss did not improve from 0.16542
72/72 [==============================] - 207s 3s/step - loss: 0.1250 - tversky: 0.9373 - val_loss: 0.1799 - val_tversky: 0.8982 - lr: 0.0500
Epoch 27/60
72/72 [==============================] - ETA: 0s - loss: 0.1226 - tversky: 0.9388
Epoch 00027: val_loss did not improve from 0.16542
72/72 [==============================] - 205s 3s/step - loss: 0.1226 - tversky: 0.9388 - val_loss: 0.1835 - val_tversky: 0.8949 - lr: 0.0500
Epoch 28/60
72/72 [==============================] - ETA: 0s - loss: 0.1292 - tversky: 0.9344
Epoch 00028: val_loss did not improve from 0.16542
72/72 [==============================] - 207s 3s/step - loss: 0.1292 - tversky: 0.9344 - val_loss: 0.1730 - val_tversky: 0.9025 - lr: 0.0500
Epoch 29/60
72/72 [==============================] - ETA: 0s - loss: 0.1199 - tversky: 0.9406
Epoch 00029: val_loss improved from 0.16542 to 0.16378, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 206s 3s/step - loss: 0.1199 - tversky: 0.9406 - val_loss: 0.1638 - val_tversky: 0.9100 - lr: 0.0500
Epoch 30/60
72/72 [==============================] - ETA: 0s - loss: 0.1169 - tversky: 0.9425
Epoch 00030: val_loss improved from 0.16378 to 0.15314, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 209s 3s/step - loss: 0.1169 - tversky: 0.9425 - val_loss: 0.1531 - val_tversky: 0.9178 - lr: 0.0500
Epoch 31/60
72/72 [==============================] - ETA: 0s - loss: 0.1188 - tversky: 0.9413
Epoch 00031: val_loss did not improve from 0.15314
72/72 [==============================] - 205s 3s/step - loss: 0.1188 - tversky: 0.9413 - val_loss: 0.1826 - val_tversky: 0.8940 - lr: 0.0500
Epoch 32/60
72/72 [==============================] - ETA: 0s - loss: 0.1111 - tversky: 0.9463
Epoch 00032: val_loss did not improve from 0.15314
72/72 [==============================] - 205s 3s/step - loss: 0.1111 - tversky: 0.9463 - val_loss: 0.1721 - val_tversky: 0.9040 - lr: 0.0500
Epoch 33/60
72/72 [==============================] - ETA: 0s - loss: 0.1099 - tversky: 0.9471
Epoch 00033: val_loss did not improve from 0.15314
72/72 [==============================] - 205s 3s/step - loss: 0.1099 - tversky: 0.9471 - val_loss: 0.1637 - val_tversky: 0.9101 - lr: 0.0500
Epoch 34/60
72/72 [==============================] - ETA: 0s - loss: 0.1078 - tversky: 0.9485
Epoch 00034: val_loss did not improve from 0.15314
72/72 [==============================] - 204s 3s/step - loss: 0.1078 - tversky: 0.9485 - val_loss: 0.1841 - val_tversky: 0.8945 - lr: 0.0500
Epoch 35/60
72/72 [==============================] - ETA: 0s - loss: 0.1075 - tversky: 0.9485
Epoch 00035: val_loss did not improve from 0.15314
72/72 [==============================] - 207s 3s/step - loss: 0.1075 - tversky: 0.9485 - val_loss: 0.1794 - val_tversky: 0.8981 - lr: 0.0500
Epoch 36/60
72/72 [==============================] - ETA: 0s - loss: 0.1020 - tversky: 0.9521
Epoch 00036: val_loss did not improve from 0.15314
72/72 [==============================] - 206s 3s/step - loss: 0.1020 - tversky: 0.9521 - val_loss: 0.1653 - val_tversky: 0.9090 - lr: 0.0500
Epoch 37/60
72/72 [==============================] - ETA: 0s - loss: 0.1007 - tversky: 0.9529
Epoch 00037: val_loss did not improve from 0.15314
72/72 [==============================] - 205s 3s/step - loss: 0.1007 - tversky: 0.9529 - val_loss: 0.1722 - val_tversky: 0.9033 - lr: 0.0500
Epoch 38/60
72/72 [==============================] - ETA: 0s - loss: 0.1009 - tversky: 0.9529
Epoch 00038: val_loss did not improve from 0.15314
72/72 [==============================] - 205s 3s/step - loss: 0.1009 - tversky: 0.9529 - val_loss: 0.1736 - val_tversky: 0.9020 - lr: 0.0500
Epoch 39/60
72/72 [==============================] - ETA: 0s - loss: 0.0978 - tversky: 0.9548
Epoch 00039: val_loss improved from 0.15314 to 0.15117, saving model to ResUNet-segModel-weights.hdf5
72/72 [==============================] - 207s 3s/step - loss: 0.0978 - tversky: 0.9548 - val_loss: 0.1512 - val_tversky: 0.9191 - lr: 0.0500
Epoch 40/60
72/72 [==============================] - ETA: 0s - loss: 0.0947 - tversky: 0.9567
Epoch 00040: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0947 - tversky: 0.9567 - val_loss: 0.1689 - val_tversky: 0.9061 - lr: 0.0500
Epoch 41/60
72/72 [==============================] - ETA: 0s - loss: 0.0986 - tversky: 0.9543
Epoch 00041: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0986 - tversky: 0.9543 - val_loss: 0.1593 - val_tversky: 0.9133 - lr: 0.0500
Epoch 42/60
72/72 [==============================] - ETA: 0s - loss: 0.0941 - tversky: 0.9571
Epoch 00042: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0941 - tversky: 0.9571 - val_loss: 0.1679 - val_tversky: 0.9066 - lr: 0.0500
Epoch 43/60
72/72 [==============================] - ETA: 0s - loss: 0.0924 - tversky: 0.9581
Epoch 00043: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0924 - tversky: 0.9581 - val_loss: 0.2040 - val_tversky: 0.8797 - lr: 0.0500
Epoch 44/60
72/72 [==============================] - ETA: 0s - loss: 0.0959 - tversky: 0.9559
Epoch 00044: val_loss did not improve from 0.15117
72/72 [==============================] - 209s 3s/step - loss: 0.0959 - tversky: 0.9559 - val_loss: 0.1651 - val_tversky: 0.9088 - lr: 0.0500
Epoch 45/60
72/72 [==============================] - ETA: 0s - loss: 0.0932 - tversky: 0.9576
Epoch 00045: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0932 - tversky: 0.9576 - val_loss: 0.1518 - val_tversky: 0.9185 - lr: 0.0500
Epoch 46/60
72/72 [==============================] - ETA: 0s - loss: 0.0912 - tversky: 0.9588
Epoch 00046: val_loss did not improve from 0.15117
72/72 [==============================] - 205s 3s/step - loss: 0.0912 - tversky: 0.9588 - val_loss: 0.1596 - val_tversky: 0.9130 - lr: 0.0500
Epoch 47/60
72/72 [==============================] - ETA: 0s - loss: 0.0967 - tversky: 0.9553
Epoch 00047: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0967 - tversky: 0.9553 - val_loss: 0.1852 - val_tversky: 0.8941 - lr: 0.0500
Epoch 48/60
72/72 [==============================] - ETA: 0s - loss: 0.0937 - tversky: 0.9573
Epoch 00048: val_loss did not improve from 0.15117
72/72 [==============================] - 208s 3s/step - loss: 0.0937 - tversky: 0.9573 - val_loss: 0.1543 - val_tversky: 0.9172 - lr: 0.0500
Epoch 49/60
72/72 [==============================] - ETA: 0s - loss: 0.0878 - tversky: 0.9609
Epoch 00049: val_loss did not improve from 0.15117

Epoch 00049: ReduceLROnPlateau reducing learning rate to 0.010000000149011612.
72/72 [==============================] - 206s 3s/step - loss: 0.0878 - tversky: 0.9609 - val_loss: 0.1729 - val_tversky: 0.9034 - lr: 0.0500
Epoch 50/60
72/72 [==============================] - ETA: 0s - loss: 0.0832 - tversky: 0.9636
Epoch 00050: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0832 - tversky: 0.9636 - val_loss: 0.1601 - val_tversky: 0.9123 - lr: 0.0100
Epoch 51/60
72/72 [==============================] - ETA: 0s - loss: 0.0797 - tversky: 0.9656
Epoch 00051: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0797 - tversky: 0.9656 - val_loss: 0.1675 - val_tversky: 0.9068 - lr: 0.0100
Epoch 52/60
72/72 [==============================] - ETA: 0s - loss: 0.0789 - tversky: 0.9660
Epoch 00052: val_loss did not improve from 0.15117
72/72 [==============================] - 205s 3s/step - loss: 0.0789 - tversky: 0.9660 - val_loss: 0.1665 - val_tversky: 0.9073 - lr: 0.0100
Epoch 53/60
72/72 [==============================] - ETA: 0s - loss: 0.0778 - tversky: 0.9667
Epoch 00053: val_loss did not improve from 0.15117
72/72 [==============================] - 208s 3s/step - loss: 0.0778 - tversky: 0.9667 - val_loss: 0.1592 - val_tversky: 0.9135 - lr: 0.0100
Epoch 54/60
72/72 [==============================] - ETA: 0s - loss: 0.0769 - tversky: 0.9672
Epoch 00054: val_loss did not improve from 0.15117
72/72 [==============================] - 209s 3s/step - loss: 0.0769 - tversky: 0.9672 - val_loss: 0.1615 - val_tversky: 0.9118 - lr: 0.0100
Epoch 55/60
72/72 [==============================] - ETA: 0s - loss: 0.0771 - tversky: 0.9670
Epoch 00055: val_loss did not improve from 0.15117
72/72 [==============================] - 208s 3s/step - loss: 0.0771 - tversky: 0.9670 - val_loss: 0.1550 - val_tversky: 0.9163 - lr: 0.0100
Epoch 56/60
72/72 [==============================] - ETA: 0s - loss: 0.0762 - tversky: 0.9676
Epoch 00056: val_loss did not improve from 0.15117
72/72 [==============================] - 206s 3s/step - loss: 0.0762 - tversky: 0.9676 - val_loss: 0.1625 - val_tversky: 0.9111 - lr: 0.0100
Epoch 57/60
72/72 [==============================] - ETA: 0s - loss: 0.0757 - tversky: 0.9679
Epoch 00057: val_loss did not improve from 0.15117
72/72 [==============================] - 209s 3s/step - loss: 0.0757 - tversky: 0.9679 - val_loss: 0.1559 - val_tversky: 0.9158 - lr: 0.0100
Epoch 58/60
72/72 [==============================] - ETA: 0s - loss: 0.0747 - tversky: 0.9685
Epoch 00058: val_loss did not improve from 0.15117
72/72 [==============================] - 209s 3s/step - loss: 0.0747 - tversky: 0.9685 - val_loss: 0.1624 - val_tversky: 0.9109 - lr: 0.0100
Epoch 59/60
72/72 [==============================] - ETA: 0s - loss: 0.0749 - tversky: 0.9684
Epoch 00059: val_loss did not improve from 0.15117

Epoch 00059: ReduceLROnPlateau reducing learning rate to 0.0019999999552965165.
72/72 [==============================] - 207s 3s/step - loss: 0.0749 - tversky: 0.9684 - val_loss: 0.1539 - val_tversky: 0.9172 - lr: 0.0100
Epoch 00059: early stopping


seg_model_json = seg_model.to_json()
with open("ResUNet-seg-model.json", "w") as json_file:
    json_file.write(seg_model_json)


h.history.keys()

dict_keys(['loss', 'tversky', 'val_loss', 'val_tversky', 'lr'])


plt.figure(figsize=(12,5))
plt.subplot(1,2,1)
plt.plot(h.history['loss']);
plt.plot(h.history['val_loss']);
plt.title("SEG Model focal tversky Loss");
plt.ylabel("focal tversky loss");
plt.xlabel("Epochs");
plt.legend(['train', 'val']);

plt.subplot(1,2,2)
plt.plot(h.history['tversky']);
plt.plot(h.history['val_tversky']);
plt.title("SEG Model tversky score");
plt.ylabel("tversky Accuracy");
plt.xlabel("Epochs");
plt.legend(['train', 'val']);


with open('clf-resnet-model.json', 'r') as json_file:
    json_savedModel= json_file.read()
#load the model architecture 
model = tf.keras.models.model_from_json(json_savedModel)
model.summary()

Model: "model"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_1 (InputLayer)           [(None, 256, 256, 3  0           []                               
                                )]                                                                
                                                                                                  
 conv1_pad (ZeroPadding2D)      (None, 262, 262, 3)  0           ['input_1[0][0]']                
                                                                                                  
 conv1_conv (Conv2D)            (None, 128, 128, 64  9472        ['conv1_pad[0][0]']              
                                )                                                                 
                                                                                                  
 conv1_bn (BatchNormalization)  (None, 128, 128, 64  256         ['conv1_conv[0][0]']             
                                )                                                                 
                                                                                                  
 conv1_relu (Activation)        (None, 128, 128, 64  0           ['conv1_bn[0][0]']               
                                )                                                                 
                                                                                                  
 pool1_pad (ZeroPadding2D)      (None, 130, 130, 64  0           ['conv1_relu[0][0]']             
                                )                                                                 
                                                                                                  
 pool1_pool (MaxPooling2D)      (None, 64, 64, 64)   0           ['pool1_pad[0][0]']              
                                                                                                  
 conv2_block1_1_conv (Conv2D)   (None, 64, 64, 64)   4160        ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block1_1_relu[0][0]']    
                                                                                                  
 conv2_block1_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_0_conv (Conv2D)   (None, 64, 64, 256)  16640       ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block1_2_relu[0][0]']    
                                                                                                  
 conv2_block1_0_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_0_bn[0][0]',      
                                                                  'conv2_block1_3_bn[0][0]']      
                                                                                                  
 conv2_block1_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block1_add[0][0]']       
                                                                                                  
 conv2_block2_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block1_out[0][0]']       
                                                                                                  
 conv2_block2_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block2_1_relu[0][0]']    
                                                                                                  
 conv2_block2_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block2_2_relu[0][0]']    
                                                                                                  
 conv2_block2_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_out[0][0]',       
                                                                  'conv2_block2_3_bn[0][0]']      
                                                                                                  
 conv2_block2_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block2_add[0][0]']       
                                                                                                  
 conv2_block3_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block2_out[0][0]']       
                                                                                                  
 conv2_block3_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block3_1_relu[0][0]']    
                                                                                                  
 conv2_block3_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block3_2_relu[0][0]']    
                                                                                                  
 conv2_block3_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_add (Add)         (None, 64, 64, 256)  0           ['conv2_block2_out[0][0]',       
                                                                  'conv2_block3_3_bn[0][0]']      
                                                                                                  
 conv2_block3_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block3_add[0][0]']       
                                                                                                  
 conv3_block1_1_conv (Conv2D)   (None, 32, 32, 128)  32896       ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block1_1_relu[0][0]']    
                                                                                                  
 conv3_block1_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_0_conv (Conv2D)   (None, 32, 32, 512)  131584      ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block1_2_relu[0][0]']    
                                                                                                  
 conv3_block1_0_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_0_bn[0][0]',      
                                                                  'conv3_block1_3_bn[0][0]']      
                                                                                                  
 conv3_block1_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block1_add[0][0]']       
                                                                                                  
 conv3_block2_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block1_out[0][0]']       
                                                                                                  
 conv3_block2_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block2_1_relu[0][0]']    
                                                                                                  
 conv3_block2_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block2_2_relu[0][0]']    
                                                                                                  
 conv3_block2_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_out[0][0]',       
                                                                  'conv3_block2_3_bn[0][0]']      
                                                                                                  
 conv3_block2_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block2_add[0][0]']       
                                                                                                  
 conv3_block3_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block2_out[0][0]']       
                                                                                                  
 conv3_block3_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block3_1_relu[0][0]']    
                                                                                                  
 conv3_block3_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block3_2_relu[0][0]']    
                                                                                                  
 conv3_block3_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_add (Add)         (None, 32, 32, 512)  0           ['conv3_block2_out[0][0]',       
                                                                  'conv3_block3_3_bn[0][0]']      
                                                                                                  
 conv3_block3_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block3_add[0][0]']       
                                                                                                  
 conv3_block4_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block3_out[0][0]']       
                                                                                                  
 conv3_block4_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block4_1_relu[0][0]']    
                                                                                                  
 conv3_block4_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block4_2_relu[0][0]']    
                                                                                                  
 conv3_block4_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block4_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_add (Add)         (None, 32, 32, 512)  0           ['conv3_block3_out[0][0]',       
                                                                  'conv3_block4_3_bn[0][0]']      
                                                                                                  
 conv3_block4_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block4_add[0][0]']       
                                                                                                  
 conv4_block1_1_conv (Conv2D)   (None, 16, 16, 256)  131328      ['conv3_block4_out[0][0]']       
                                                                                                  
 conv4_block1_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block1_1_relu[0][0]']    
                                                                                                  
 conv4_block1_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_0_conv (Conv2D)   (None, 16, 16, 1024  525312      ['conv3_block4_out[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block1_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block1_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block1_0_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_0_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_0_bn[0][0]',      
                                )                                 'conv4_block1_3_bn[0][0]']      
                                                                                                  
 conv4_block1_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block1_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block2_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block1_out[0][0]']       
                                                                                                  
 conv4_block2_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block2_1_relu[0][0]']    
                                                                                                  
 conv4_block2_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block2_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block2_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block2_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block2_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_out[0][0]',       
                                )                                 'conv4_block2_3_bn[0][0]']      
                                                                                                  
 conv4_block2_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block2_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block3_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block2_out[0][0]']       
                                                                                                  
 conv4_block3_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block3_1_relu[0][0]']    
                                                                                                  
 conv4_block3_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block3_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block3_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block3_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block3_add (Add)         (None, 16, 16, 1024  0           ['conv4_block2_out[0][0]',       
                                )                                 'conv4_block3_3_bn[0][0]']      
                                                                                                  
 conv4_block3_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block3_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block4_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block3_out[0][0]']       
                                                                                                  
 conv4_block4_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block4_1_relu[0][0]']    
                                                                                                  
 conv4_block4_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block4_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block4_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block4_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block4_add (Add)         (None, 16, 16, 1024  0           ['conv4_block3_out[0][0]',       
                                )                                 'conv4_block4_3_bn[0][0]']      
                                                                                                  
 conv4_block4_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block4_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block5_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block4_out[0][0]']       
                                                                                                  
 conv4_block5_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block5_1_relu[0][0]']    
                                                                                                  
 conv4_block5_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block5_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block5_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block5_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block5_add (Add)         (None, 16, 16, 1024  0           ['conv4_block4_out[0][0]',       
                                )                                 'conv4_block5_3_bn[0][0]']      
                                                                                                  
 conv4_block5_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block5_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block6_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block5_out[0][0]']       
                                                                                                  
 conv4_block6_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block6_1_relu[0][0]']    
                                                                                                  
 conv4_block6_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block6_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block6_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block6_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block6_add (Add)         (None, 16, 16, 1024  0           ['conv4_block5_out[0][0]',       
                                )                                 'conv4_block6_3_bn[0][0]']      
                                                                                                  
 conv4_block6_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block6_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv5_block1_1_conv (Conv2D)   (None, 8, 8, 512)    524800      ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block1_1_relu[0][0]']    
                                                                                                  
 conv5_block1_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_0_conv (Conv2D)   (None, 8, 8, 2048)   2099200     ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    
                                                                                                  
 conv5_block1_0_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_0_bn[0][0]',      
                                                                  'conv5_block1_3_bn[0][0]']      
                                                                                                  
 conv5_block1_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block1_add[0][0]']       
                                                                                                  
 conv5_block2_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block1_out[0][0]']       
                                                                                                  
 conv5_block2_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block2_1_relu[0][0]']    
                                                                                                  
 conv5_block2_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    
                                                                                                  
 conv5_block2_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_out[0][0]',       
                                                                  'conv5_block2_3_bn[0][0]']      
                                                                                                  
 conv5_block2_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block2_add[0][0]']       
                                                                                                  
 conv5_block3_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block2_out[0][0]']       
                                                                                                  
 conv5_block3_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block3_1_relu[0][0]']    
                                                                                                  
 conv5_block3_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    
                                                                                                  
 conv5_block3_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block2_out[0][0]',       
                                                                  'conv5_block3_3_bn[0][0]']      
                                                                                                  
 conv5_block3_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block3_add[0][0]']       
                                                                                                  
 average_pooling2d (AveragePool  (None, 2, 2, 2048)  0           ['conv5_block3_out[0][0]']       
 ing2D)                                                                                           
                                                                                                  
 Flatten (Flatten)              (None, 8192)         0           ['average_pooling2d[0][0]']      
                                                                                                  
 dense (Dense)                  (None, 256)          2097408     ['Flatten[0][0]']                
                                                                                                  
 dropout (Dropout)              (None, 256)          0           ['dense[0][0]']                  
                                                                                                  
 dense_1 (Dense)                (None, 256)          65792       ['dropout[0][0]']                
                                                                                                  
 dropout_1 (Dropout)            (None, 256)          0           ['dense_1[0][0]']                
                                                                                                  
 dense_2 (Dense)                (None, 2)            514         ['dropout_1[0][0]']              
                                                                                                  
==================================================================================================
Total params: 25,751,426
Trainable params: 25,698,306
Non-trainable params: 53,120
__________________________________________________________________________________________________


model.load_weights('clf-resnet-weights.hdf5')


model.compile(loss = 'categorical_crossentropy', 
              optimizer='adam', 
              metrics= ["accuracy"]
             )
model.summary()

Model: "model"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_1 (InputLayer)           [(None, 256, 256, 3  0           []                               
                                )]                                                                
                                                                                                  
 conv1_pad (ZeroPadding2D)      (None, 262, 262, 3)  0           ['input_1[0][0]']                
                                                                                                  
 conv1_conv (Conv2D)            (None, 128, 128, 64  9472        ['conv1_pad[0][0]']              
                                )                                                                 
                                                                                                  
 conv1_bn (BatchNormalization)  (None, 128, 128, 64  256         ['conv1_conv[0][0]']             
                                )                                                                 
                                                                                                  
 conv1_relu (Activation)        (None, 128, 128, 64  0           ['conv1_bn[0][0]']               
                                )                                                                 
                                                                                                  
 pool1_pad (ZeroPadding2D)      (None, 130, 130, 64  0           ['conv1_relu[0][0]']             
                                )                                                                 
                                                                                                  
 pool1_pool (MaxPooling2D)      (None, 64, 64, 64)   0           ['pool1_pad[0][0]']              
                                                                                                  
 conv2_block1_1_conv (Conv2D)   (None, 64, 64, 64)   4160        ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block1_1_relu[0][0]']    
                                                                                                  
 conv2_block1_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block1_0_conv (Conv2D)   (None, 64, 64, 256)  16640       ['pool1_pool[0][0]']             
                                                                                                  
 conv2_block1_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block1_2_relu[0][0]']    
                                                                                                  
 conv2_block1_0_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block1_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_0_bn[0][0]',      
                                                                  'conv2_block1_3_bn[0][0]']      
                                                                                                  
 conv2_block1_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block1_add[0][0]']       
                                                                                                  
 conv2_block2_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block1_out[0][0]']       
                                                                                                  
 conv2_block2_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block2_1_relu[0][0]']    
                                                                                                  
 conv2_block2_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block2_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block2_2_relu[0][0]']    
                                                                                                  
 conv2_block2_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block2_add (Add)         (None, 64, 64, 256)  0           ['conv2_block1_out[0][0]',       
                                                                  'conv2_block2_3_bn[0][0]']      
                                                                                                  
 conv2_block2_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block2_add[0][0]']       
                                                                                                  
 conv2_block3_1_conv (Conv2D)   (None, 64, 64, 64)   16448       ['conv2_block2_out[0][0]']       
                                                                                                  
 conv2_block3_1_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_1_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_2_conv (Conv2D)   (None, 64, 64, 64)   36928       ['conv2_block3_1_relu[0][0]']    
                                                                                                  
 conv2_block3_2_bn (BatchNormal  (None, 64, 64, 64)  256         ['conv2_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_2_relu (Activatio  (None, 64, 64, 64)  0           ['conv2_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv2_block3_3_conv (Conv2D)   (None, 64, 64, 256)  16640       ['conv2_block3_2_relu[0][0]']    
                                                                                                  
 conv2_block3_3_bn (BatchNormal  (None, 64, 64, 256)  1024       ['conv2_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv2_block3_add (Add)         (None, 64, 64, 256)  0           ['conv2_block2_out[0][0]',       
                                                                  'conv2_block3_3_bn[0][0]']      
                                                                                                  
 conv2_block3_out (Activation)  (None, 64, 64, 256)  0           ['conv2_block3_add[0][0]']       
                                                                                                  
 conv3_block1_1_conv (Conv2D)   (None, 32, 32, 128)  32896       ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block1_1_relu[0][0]']    
                                                                                                  
 conv3_block1_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block1_0_conv (Conv2D)   (None, 32, 32, 512)  131584      ['conv2_block3_out[0][0]']       
                                                                                                  
 conv3_block1_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block1_2_relu[0][0]']    
                                                                                                  
 conv3_block1_0_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block1_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_0_bn[0][0]',      
                                                                  'conv3_block1_3_bn[0][0]']      
                                                                                                  
 conv3_block1_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block1_add[0][0]']       
                                                                                                  
 conv3_block2_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block1_out[0][0]']       
                                                                                                  
 conv3_block2_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block2_1_relu[0][0]']    
                                                                                                  
 conv3_block2_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block2_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block2_2_relu[0][0]']    
                                                                                                  
 conv3_block2_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block2_add (Add)         (None, 32, 32, 512)  0           ['conv3_block1_out[0][0]',       
                                                                  'conv3_block2_3_bn[0][0]']      
                                                                                                  
 conv3_block2_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block2_add[0][0]']       
                                                                                                  
 conv3_block3_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block2_out[0][0]']       
                                                                                                  
 conv3_block3_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block3_1_relu[0][0]']    
                                                                                                  
 conv3_block3_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block3_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block3_2_relu[0][0]']    
                                                                                                  
 conv3_block3_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block3_add (Add)         (None, 32, 32, 512)  0           ['conv3_block2_out[0][0]',       
                                                                  'conv3_block3_3_bn[0][0]']      
                                                                                                  
 conv3_block3_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block3_add[0][0]']       
                                                                                                  
 conv3_block4_1_conv (Conv2D)   (None, 32, 32, 128)  65664       ['conv3_block3_out[0][0]']       
                                                                                                  
 conv3_block4_1_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_1_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_2_conv (Conv2D)   (None, 32, 32, 128)  147584      ['conv3_block4_1_relu[0][0]']    
                                                                                                  
 conv3_block4_2_bn (BatchNormal  (None, 32, 32, 128)  512        ['conv3_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_2_relu (Activatio  (None, 32, 32, 128)  0          ['conv3_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv3_block4_3_conv (Conv2D)   (None, 32, 32, 512)  66048       ['conv3_block4_2_relu[0][0]']    
                                                                                                  
 conv3_block4_3_bn (BatchNormal  (None, 32, 32, 512)  2048       ['conv3_block4_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv3_block4_add (Add)         (None, 32, 32, 512)  0           ['conv3_block3_out[0][0]',       
                                                                  'conv3_block4_3_bn[0][0]']      
                                                                                                  
 conv3_block4_out (Activation)  (None, 32, 32, 512)  0           ['conv3_block4_add[0][0]']       
                                                                                                  
 conv4_block1_1_conv (Conv2D)   (None, 16, 16, 256)  131328      ['conv3_block4_out[0][0]']       
                                                                                                  
 conv4_block1_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block1_1_relu[0][0]']    
                                                                                                  
 conv4_block1_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block1_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block1_0_conv (Conv2D)   (None, 16, 16, 1024  525312      ['conv3_block4_out[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block1_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block1_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block1_0_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_0_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block1_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block1_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_0_bn[0][0]',      
                                )                                 'conv4_block1_3_bn[0][0]']      
                                                                                                  
 conv4_block1_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block1_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block2_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block1_out[0][0]']       
                                                                                                  
 conv4_block2_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block2_1_relu[0][0]']    
                                                                                                  
 conv4_block2_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block2_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block2_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block2_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block2_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block2_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block2_add (Add)         (None, 16, 16, 1024  0           ['conv4_block1_out[0][0]',       
                                )                                 'conv4_block2_3_bn[0][0]']      
                                                                                                  
 conv4_block2_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block2_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block3_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block2_out[0][0]']       
                                                                                                  
 conv4_block3_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block3_1_relu[0][0]']    
                                                                                                  
 conv4_block3_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block3_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block3_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block3_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block3_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block3_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block3_add (Add)         (None, 16, 16, 1024  0           ['conv4_block2_out[0][0]',       
                                )                                 'conv4_block3_3_bn[0][0]']      
                                                                                                  
 conv4_block3_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block3_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block4_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block3_out[0][0]']       
                                                                                                  
 conv4_block4_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block4_1_relu[0][0]']    
                                                                                                  
 conv4_block4_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block4_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block4_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block4_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block4_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block4_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block4_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block4_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block4_add (Add)         (None, 16, 16, 1024  0           ['conv4_block3_out[0][0]',       
                                )                                 'conv4_block4_3_bn[0][0]']      
                                                                                                  
 conv4_block4_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block4_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block5_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block4_out[0][0]']       
                                                                                                  
 conv4_block5_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block5_1_relu[0][0]']    
                                                                                                  
 conv4_block5_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block5_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block5_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block5_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block5_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block5_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block5_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block5_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block5_add (Add)         (None, 16, 16, 1024  0           ['conv4_block4_out[0][0]',       
                                )                                 'conv4_block5_3_bn[0][0]']      
                                                                                                  
 conv4_block5_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block5_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv4_block6_1_conv (Conv2D)   (None, 16, 16, 256)  262400      ['conv4_block5_out[0][0]']       
                                                                                                  
 conv4_block6_1_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_1_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_2_conv (Conv2D)   (None, 16, 16, 256)  590080      ['conv4_block6_1_relu[0][0]']    
                                                                                                  
 conv4_block6_2_bn (BatchNormal  (None, 16, 16, 256)  1024       ['conv4_block6_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv4_block6_2_relu (Activatio  (None, 16, 16, 256)  0          ['conv4_block6_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv4_block6_3_conv (Conv2D)   (None, 16, 16, 1024  263168      ['conv4_block6_2_relu[0][0]']    
                                )                                                                 
                                                                                                  
 conv4_block6_3_bn (BatchNormal  (None, 16, 16, 1024  4096       ['conv4_block6_3_conv[0][0]']    
 ization)                       )                                                                 
                                                                                                  
 conv4_block6_add (Add)         (None, 16, 16, 1024  0           ['conv4_block5_out[0][0]',       
                                )                                 'conv4_block6_3_bn[0][0]']      
                                                                                                  
 conv4_block6_out (Activation)  (None, 16, 16, 1024  0           ['conv4_block6_add[0][0]']       
                                )                                                                 
                                                                                                  
 conv5_block1_1_conv (Conv2D)   (None, 8, 8, 512)    524800      ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block1_1_relu[0][0]']    
                                                                                                  
 conv5_block1_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block1_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block1_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block1_0_conv (Conv2D)   (None, 8, 8, 2048)   2099200     ['conv4_block6_out[0][0]']       
                                                                                                  
 conv5_block1_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    
                                                                                                  
 conv5_block1_0_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_0_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block1_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block1_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_0_bn[0][0]',      
                                                                  'conv5_block1_3_bn[0][0]']      
                                                                                                  
 conv5_block1_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block1_add[0][0]']       
                                                                                                  
 conv5_block2_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block1_out[0][0]']       
                                                                                                  
 conv5_block2_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block2_1_relu[0][0]']    
                                                                                                  
 conv5_block2_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block2_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block2_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block2_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    
                                                                                                  
 conv5_block2_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block2_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block2_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block1_out[0][0]',       
                                                                  'conv5_block2_3_bn[0][0]']      
                                                                                                  
 conv5_block2_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block2_add[0][0]']       
                                                                                                  
 conv5_block3_1_conv (Conv2D)   (None, 8, 8, 512)    1049088     ['conv5_block2_out[0][0]']       
                                                                                                  
 conv5_block3_1_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_1_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_1_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_1_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_2_conv (Conv2D)   (None, 8, 8, 512)    2359808     ['conv5_block3_1_relu[0][0]']    
                                                                                                  
 conv5_block3_2_bn (BatchNormal  (None, 8, 8, 512)   2048        ['conv5_block3_2_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_2_relu (Activatio  (None, 8, 8, 512)   0           ['conv5_block3_2_bn[0][0]']      
 n)                                                                                               
                                                                                                  
 conv5_block3_3_conv (Conv2D)   (None, 8, 8, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    
                                                                                                  
 conv5_block3_3_bn (BatchNormal  (None, 8, 8, 2048)  8192        ['conv5_block3_3_conv[0][0]']    
 ization)                                                                                         
                                                                                                  
 conv5_block3_add (Add)         (None, 8, 8, 2048)   0           ['conv5_block2_out[0][0]',       
                                                                  'conv5_block3_3_bn[0][0]']      
                                                                                                  
 conv5_block3_out (Activation)  (None, 8, 8, 2048)   0           ['conv5_block3_add[0][0]']       
                                                                                                  
 average_pooling2d (AveragePool  (None, 2, 2, 2048)  0           ['conv5_block3_out[0][0]']       
 ing2D)                                                                                           
                                                                                                  
 Flatten (Flatten)              (None, 8192)         0           ['average_pooling2d[0][0]']      
                                                                                                  
 dense (Dense)                  (None, 256)          2097408     ['Flatten[0][0]']                
                                                                                                  
 dropout (Dropout)              (None, 256)          0           ['dense[0][0]']                  
                                                                                                  
 dense_1 (Dense)                (None, 256)          65792       ['dropout[0][0]']                
                                                                                                  
 dropout_1 (Dropout)            (None, 256)          0           ['dense_1[0][0]']                
                                                                                                  
 dense_2 (Dense)                (None, 2)            514         ['dropout_1[0][0]']              
                                                                                                  
==================================================================================================
Total params: 25,751,426
Trainable params: 25,698,306
Non-trainable params: 53,120
__________________________________________________________________________________________________


prediction = model.predict(test_generator)

pred = np.argmax(prediction, axis=1)
#pred = np.asarray(pred).astype('str')
original = np.asarray(test['mask']).astype('int')

from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
accuracy = accuracy_score(original, pred)
print(accuracy)

cm = confusion_matrix(original, pred)

report = classification_report(original, pred, labels = [0,1])
print(report)
plt.figure(figsize = (5,5))
sns.heatmap(cm, annot=True);

0.9745762711864406
              precision    recall  f1-score   support

           0       0.97      0.99      0.98       375
           1       0.99      0.94      0.96       215

    accuracy                           0.97       590
   macro avg       0.98      0.97      0.97       590
weighted avg       0.97      0.97      0.97       590


test_ids = list(X_test.image_path)
test_mask = list(X_test.mask_path)
test_data = DataGenerator(test_ids, test_mask)
_, tv = seg_model.evaluate(test_data)
print("Segmentation tversky is {:.2f}%".format(tv*100))

6/6 [==============================] - 4s 587ms/step - loss: 0.1688 - tversky: 0.9064
Segmentation tversky is 90.64%


def prediction(test, model, model_seg):
    '''
    Predcition function which takes dataframe containing ImageID as Input and perform 2 type of prediction on the image
    Initially, image is passed through the classification network which predicts whether the image has defect or not, if the model
    is 99% sure that the image has no defect, then the image is labeled as no-defect, if the model is not sure, it passes the image to the
    segmentation network, it again checks if the image has defect or not, if it has defect, then the type and location of defect is found
    '''
    # empty list to store results
    mask, image_id, has_mask = [], [], []
    
    #itetrating through each image in test data
    for i in test.image_path:
        
        img = io.imread(i)
        #normalizing
        img = img *1./255.
        #reshaping
        img = cv2.resize(img, (256,256))
        # converting img into array
        img = np.array(img, dtype=np.float64)
        #reshaping the image from 256,256,3 to 1,256,256,3
        img = np.reshape(img, (1,256,256,3))
        
        #making prediction for tumor in image
        is_defect = model.predict(img)
        
        #if tumour is not present we append the details of the image to the list
        if np.argmax(is_defect)==0:
            image_id.append(i)
            has_mask.append(0)
            mask.append('No mask :)')
            continue
        
        #Creating a empty array of shape 1,256,256,1
        X = np.empty((1,256,256,3))
        # read the image
        img = io.imread(i)
        #resizing the image and coverting them to array of type float64
        img = cv2.resize(img, (256,256))
        img = np.array(img, dtype=np.float64)
        
        # standardising the image
        img -= img.mean()
        img /= img.std()
        #converting the shape of image from 256,256,3 to 1,256,256,3
        X[0,] = img
        
        #make prediction of mask
        predict = model_seg.predict(X)
        
        # if sum of predicted mask is 0 then there is not tumour
        if predict.round().astype(int).sum()==0:
            image_id.append(i)
            has_mask.append(0)
            mask.append('No mask :)')
        else:
        #if the sum of pixel values are more than 0, then there is tumour
            image_id.append(i)
            has_mask.append(1)
            mask.append(predict)
            
    return pd.DataFrame({'image_path': image_id,'predicted_mask': mask,'has_mask': has_mask})


# making prediction
df_pred = prediction(test, model, seg_model)
df_pred


# merging original and prediction df
df_pred = test.merge(df_pred, on='image_path')
df_pred.head(10)


#visualizing prediction
count = 0
fig, axs = plt.subplots(15,5, figsize=(30,70))

for i in range(len(df_pred)):
    if df_pred.has_mask[i]==1 and count<15:
        #read mri images
        img = io.imread(df_pred.image_path[i])
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        axs[count][0].imshow(img)
        axs[count][0].title.set_text('Brain MRI')
        
        #read original mask
        mask = io.imread(df_pred.mask_path[i])
        axs[count][1].imshow(mask)
        axs[count][1].title.set_text('Original Mask')
        
        #read predicted mask
        pred = np.array(df_pred.predicted_mask[i]).squeeze().round()
        axs[count][2].imshow(pred)
        axs[count][2].title.set_text('AI predicted mask')
        
        #overlay original mask with MRI
        img[mask==255] = (255,0,0)
        axs[count][3].imshow(img)
        axs[count][3].title.set_text('Brain MRI with original mask (Ground Truth)')
        
        #overlay predicted mask and MRI
        img_ = io.imread(df_pred.image_path[i])
        img_ = cv2.cvtColor(img_, cv2.COLOR_BGR2RGB)
        img_[pred==1] = (0,255,150)
        axs[count][4].imshow(img_)
        axs[count][4].title.set_text('MRI with AI PREDICTED MASK')
        
        count +=1
    if (count==15):
        break

fig.tight_layout()

	patient_id	path
0	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...
1	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...
2	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...
3	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...
4	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...

	patient_id	image_path	mask_path	mask
0	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
1	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
2	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
3	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
4	kaggle_3m\TCGA_CS_4941_19960909	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
...	...	...	...	...
3924	kaggle_3m\TCGA_HT_A61B_19991127	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
3925	kaggle_3m\TCGA_HT_A61B_19991127	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
3926	kaggle_3m\TCGA_HT_A61B_19991127	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
3927	kaggle_3m\TCGA_HT_A61B_19991127	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0
3928	kaggle_3m\TCGA_HT_A61B_19991127	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0

	image_path	predicted_mask	has_mask
0	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
1	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	[[[[4.6963205e-08], [5.0886354e-07], [1.121319...	1
2	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
3	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
4	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	[[[[5.3284335e-08], [2.4559512e-07], [4.543847...	1
...	...	...	...
585	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
586	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
587	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	[[[[3.895526e-08], [4.4806472e-07], [8.1248714...	1
588	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0
589	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	No mask :)	0

	image_path	mask_path	mask	predicted_mask	has_mask
0	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
1	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	1	[[[[4.6963205e-08], [5.0886354e-07], [1.121319...	1
2	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
3	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
4	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	1	[[[[5.3284335e-08], [2.4559512e-07], [4.543847...	1
5	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
6	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
7	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	1	[[[[5.2790874e-08], [2.507918e-07], [4.4831563...	1
8	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	0	No mask :)	0
9	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	../desktop/lgg-mri-segmentation/kaggle_3m\TCGA...	1	[[[[4.43354e-08], [2.4883016e-07], [5.5490364e...	1